Linkage maps of the Atlantic salmon (Salmo salar) genome derived from RAD sequencing

Abstract

Background: Genetic linkage maps are useful tools for mapping quantitative trait loci (QTL) influencing variation in traits of interest in a population. Genotyping-by-sequencing approaches such as Restriction-site Associated DNA sequencing (RAD-Seq) now enable the rapid discovery and genotyping of genome-wide SNP markers suitable for the development of dense SNP linkage maps, including in non-model organisms such as Atlantic salmon (Salmo salar). This paper describes the development and characterisation of a high density SNP linkage map based on SbfI RAD-Seq SNP markers from two Atlantic salmon reference families.

Results: Approximately 6,000 SNPs were assigned to 29 linkage groups, utilising markers from known genomic locations as anchors. Linkage maps were then constructed for the four mapping parents separately. Overall map lengths were comparable between male and female parents, but the distribution of the SNPs showed sex-specific patterns with a greater degree of clustering of sire-segregating SNPs to single chromosome regions. The maps were integrated with the Atlantic salmon draft reference genome contigs, allowing the unique assignment of ~4,000 contigs to a linkage group. 112 genome contigs mapped to two or more linkage groups, highlighting regions of putative homeology within the salmon genome. A comparative genomics analysis with the stickleback reference genome identified putative genes closely linked to approximately half of the ordered SNPs and demonstrated blocks of orthology between the Atlantic salmon and stickleback genomes. A subset of 47 RAD-Seq SNPs were successfully validated using a high-throughput genotyping assay, with a correspondence of 97% between the two assays.

Conclusions: This Atlantic salmon RAD-Seq linkage map is a resource for salmonid genomics research as genotyping-by-sequencing becomes increasingly common. This is aided by the integration of the SbfI RAD-Seq SNPs with existing reference maps and the draft reference genome, as well as the identification of putative genes proximal to the SNPs. Differences in the distribution of recombination events between the sexes is evident, and regions of homeology have been identified which are reflective of the recent salmonid whole genome duplication.

Figure 1

Relationship between read depth and call rate. The number of reads per individual following exclusion of PCR duplicates (x-axis) plotted against the proportion of SNP genotypes successfully called for all putative SNPs (y-axis). The red lines on the graph indicate the thresholds below which individuals were removed from the current analysis due to an excess of missing genotypes.

Figure 2

Example linkage maps. Maps for linkage group 13 for: (i) Br5 mother; (ii) Br5 father, (iii) Br6 mother; (iv) Br6 father. Map lengths are shorter in the male parent maps and markers are more widely spaced in the female parent maps. Marker names on the drawn maps are coded as RAD1-RADX depending on the ordered position of the marker on the linkage group.

Figure 3

Comparison of marker clustering between male and female linkage maps. For each linkage group for each parent, the five intervals with the highest percentage of markers were identified. For each of these intervals, an average percentage of markers was calculated across all linkage groups and both families Br5 and Br6. Blue bars = Male parent average percentages; Red bars = Female parent average percentages. A greater clustering of markers in interval one is apparent in male parents.

Figure 4

Distribution of RAD paired-end contig lengths. Paired-end (PE) RAD-sequencing generates a read from the P1 adaptor which is located at the restriction site and a PE contig generated from sequencing at the P2 adaptor at the sheared end of the fragment. The most frequent length of the PE contigs was between 450 and 600 bp. A small number of PE contigs were over 650 bp in length; these are not shown in the figure.

Figure 5

Comparison of the number of SNPs per linkage group with a previously published map. The number of SNPs per linkage group (assigned using the CRI-MAP software) in the current study was plotted against the number of SNPs per linkage group in the SNP map study conducted by Lien et al. [11]. The number of SNPs identified per linkage group in the two studies were highly correlated (r = 0.83).